The present invention relates to a 3-dimensional object recognition method, by use of which an object can be accurately recognized at high speed, and a bin-picking system using the same method.
In the past, various methods of recognizing 3-dimensional position and posture or the configuration of an object by use of a pair of 2-dimensional images for making a stereo image have been proposed. For example, Japanese Patent Early Publication [KOKAI] No. 10-206135 describes about xe2x80x9cDECISION METHOD FOR POSITIONAL POSTURE OF THREE-DIMENSIONAL OBJECTxe2x80x9d. In this method, an edge image is extracted from a stereo image obtained by observing a free curved-surface body that is a three-dimensional object. The edge image is divided into segments according to its local feature, and then local geometrical features are added to the segments. Next, the local geometrical features of the segments are collated initially with a local geometrical feature model of a free curved-surface body model that is previously created to detect a corresponding candidate. A small plane patch of the free curved-surface body model corresponding to the apparent contour line of the free curved-surface body is selected on the basis of the positional posture and the observation direction of the candidate. The corresponding candidate is adjusted fine by use of the selected small plane patch. The positional posture of the free curved-surface body is detected by a recognition treatment according to the fine adjustment and the initial collation described above.
On the other hand, Japanese Patent Early Publication [KOKAI] No. 8-136220 describes about xe2x80x9cMETHOD AND DEVICE FOR DETECTING POSITION OF ARTICLExe2x80x9d. In this method, feature portions such as line segments and arcs are extracted from an image obtained by picking up an object article with two cameras. By matching these feature portions with feature portions on a two-dimensional viewing-pattern model, the correspondence between the left and right images is made according to the stereoscopic measuring principle. Three-dimensional positions of the feature portions are measured by use of the result of the correspondence, so that a three-dimensional structure model of the object article is established. The three-dimensional position of the object article is computed by matching the feature portions, whose three-dimensional positions are measured, with the feature portions of the three-dimensional structure model.
In addition, Japanese Patent Early Publication [KOKAI] No. 4-130587 describes about xe2x80x9cTHREE-DIMENSIONAL PICTURE EVALUATION DEVICExe2x80x9d. In this device, the position and the posture of an object are estimated according to picture information obtained by picking up the object with three TV cameras and known three-dimensional model data of the article. Then, picture information obtained when picking up the model in the estimated position and posture is predicted to obtain predicted picture information. The picture information picked up by the TV cameras is compared with the predicted picture information, and a degree of the match therebetween is determined to recognize the three-dimensional object.
Since these methods are built on premises that the information detected from the image provided by the image pickup device is correct, there is a problem that the object can not be accurately recognized when using an image with complex information obtained by picking up a scene that a plurality of objects with the same configuration are heaped up in confusion, or an image including noise. Moreover, the methods of Japanese Patent Early Publication [KOKAI] Nos. 10-206135 and 08-136220 need a repetition treatment of determining predicted values of two-dimensional features from the three-dimensional information to perform collation, correcting the estimation of the three-dimensional position and posture according to the result of collation, and predicting the two-dimensional features from the obtained three-dimensional information. Therefore, there is a problem that the treatment time is extended, so that the efficiency of recognition lowers.
Therefore, a primary object of the present invention is to provide a 3-dimensional object recognition method, by use of which three-dimensional position and posture of an object can be accurately recognized at high speed. That is, this three-dimensional object recognition method comprises:
a step (A) of taking a pair of first and second images for making a stereo image of an object;
a step (B) of detecting a two-dimensional feature of the object in each of the first and second images;
a step (D) of making a correspondence of the two-dimensional feature between the first and second images according to a stereoscopic measurement principle;
a step (F) of recognizing three-dimensional position and posture of the object according to information in three dimensions of the two-dimensional feature obtained by the correspondence; and
a step (G) of evaluating a degree of reliability of the recognized three-dimensional position and posture;
wherein the method comprises at least one of a step (C) of evaluating a degree of reliability of a result of the step (B) by comparing with known model data of the object, which is performed between the steps (B) and (D), and a step (E) of evaluating a degree of reliability of a result of the step (D) by comparing the two-dimensional feature detected in the first image with the corresponding two-dimensional feature detected in the second image, which is performed between the steps (D) and (F).
In addition, a further object of the present invention is to provide a 3-fimensional recognition method described below for accurately recognizing three-dimensional position and posture of an object at high speed. That is, the three-dimensional recognition method comprises:
a step (A) of taking a pair of first and second images for making a stereo image of an object, and a third image from a viewpoint different from them;
a step (B) of detecting a two-dimensional feature of the object in each of the first, second and third images;
a step (D) of making a correspondence of the two-dimensional feature each between the first and second images and between the first and third images according to a stereoscopic measurement principle;
a step (F) of recognizing a first candidate of three-dimensional position and posture of the object according to information in three dimensions of the two-dimensional feature obtained from the correspondence between the first and second images, and a second candidate of three-dimensional position and posture of the object according to information in three dimensions of the two-dimensional feature obtained from the correspondence between the first and third images; and
a step (G) of evaluating a degree of reliability of each of the first and second candidates;
wherein the recognition method comprises at least one of a step (C) of evaluating a degree of reliability of a result of the step (B) by comparing with model data of the object, which is performed between the steps (B) and (D), a step (E) of evaluating a degree of reliability of a result of the step (D) by comparing the two-dimensional feature detected in the first image with the corresponding two-dimensional features detected in the second and third images, which is performed between the steps (D) and (F), and a step (H) of determining three-dimensional position and posture of the object according to the first and second candidates provided from the step (G).
Another object of the present invention is to provide a bin-picking system using the 3-dimensional object recognition method mentioned above. The bin-picking system of the present invention comprises an image-processing unit for performing the 3-dimensional object recognition method mentioned above, a robot with a flexible robot arm, and a robot controller for controlling the robot according to information provided from the image-processing unit such that the robot arm picks up an object from a bin, in which a plurality of objects are heaped up in confusion, and carries the picked-up object to a required position. Therefore, even when picking up a part from a bin, in which a plurality of parts having the same configuration are heaped up in confusion, it is possible to select a part that is the easiest to pick up from the bin, and pick up the selected part. As a result, it is possible to provide efficient and accurate supply of parts in production line, while preventing the occurrence of pickup miss.